CN1522419A - Method and system for design selection by interactive visualization - Google Patents
Method and system for design selection by interactive visualization Download PDFInfo
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- CN1522419A CN1522419A CNA028119789A CN02811978A CN1522419A CN 1522419 A CN1522419 A CN 1522419A CN A028119789 A CNA028119789 A CN A028119789A CN 02811978 A CN02811978 A CN 02811978A CN 1522419 A CN1522419 A CN 1522419A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
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- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
- G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
Abstract
A method and system for electronic circuit design selection by interactive visualization. The present invention is particularly appropriate for learning the performance and behaviour of analog circuits, and for selecting a preferred design from a dataset of candidate designs derived from a multi-objective optimization. The method consists of providing a multidimensional dataset from a multiobjective optimization, or otherwise. The multidimensional dataset is then displayed as a plurality of plots. The plots can be one-dimensional, or multi-dimensional, and can include parallel coordinate plots. By modifying at least one of the plots, the user can interactively select an evaluation dataset for further evaluation or testing. The modification can take the form of interactive filtering to reduce the dataset in a desired manner. Typically, this is done through a graphical interface, by visual selection, brushing, etc. It can also include defining or constructing constraints of one or more variables in the multidimensional dataset. The constraints can include linear and non-linear. This modification and selection process can be repeated as necessary to further restrict the dataset to a manageable number of candidate designs.
Description
Technical field
The present invention relates to design system and methodology.Especially, the present invention relates to a kind of method and system of from many candidate designs schemes, selecting design proposal by interactive diagram (interactive visualization) technology.The present invention is applied to select the design proposal of simulation, numeral and mixed signal circuit especially from the candidate designs scheme of deriving by multiobjective optimization.
Background technology
Current electronic chip deviser requires to develop the effective ways that are used for information visualization and Knowledge Discovery, it makes the user of electric design automation (EDA) software and design database more directly and more effectively carry out alternately, thereby understands the performance characteristic of their design proposal.When using the multiple-objection optimization technology that very a large amount of candidate designs scheme is provided, this point is just important especially.The circuit module of determining for each candidate designs scheme provides an informative cube, but because of its scale and complexity, the deviser is difficult to choose effectively, to find the design proposal of wanting most.
Well-known is to utilize visual sensory perceptual system to observe multidimensional or multivariable data set.Have the method that is used to illustrate this data set in a large number at present, such as many views, Chernoff faces, star chart, cell mean view, Aiken and West ' s figure, John-Neyman figure, parallel coordinates, flake demonstration, dependency rule, based on the visual chart of wavelet transformation, Pixel-level and the tree derivation of multi-resolution display.Yet, the also untapped application software that goes out this system and method, with allow the eda software user by using visual interface dynamic queries candidate designs scheme master database and isolate interested design proposal.
Information visualization has become the research field of being paid close attention to day by day.It is found that such visualization technique in many application of science, engineering, management and technique of internet all of great use.For semi-conductor industry, one times of per 18 monthly increment of silicon capacity make and can set up the system that becomes increasingly complex on single silicons.Yet the designed capacity of the such complication system of design reduces along with complicacy in the rational time.As if the gap between designed capacity and the yield-power threatening the growth of semi-conductor industry.Ideally, information visualization can be used for helping effectively to make up this gap as a major part of electronic design automation tool.
Therefore need provide a kind of method and system that is used to carry out interactive diagram (visual), so that can from one group of multidimensional candidate designs scheme, select design proposal effectively, particularly in numeral or Analog Circuit Design field.
Summary of the invention
The objective of the invention is to eliminate or alleviate at least one shortcoming of previous designs method and system.
In first scheme, provide a kind of method of selecting circuit design by the interactive mode diagram method of cube.This method comprises that the employing multi-objective optimization method provides a cube, perhaps other method.Then this cube is shown as a plurality of charts.These charts can be one dimension or multidimensional, and can comprise parallel coordinates figure.By revising at least one chart, the user can alternatively select a valuation data set to be used for further valuation or test.Thereby this modification can take the mode of mutual filtering to reduce data set in the mode of wanting.Typically, can utilize visual selection, brush pen etc. to finish reducing of data set by graphical interfaces.Also can be included in the constraint function that multidimensional data is concentrated definition or created one or more variablees.This constraint can comprise linear and nonlinear constraint.This modification and selection course can repeat as required, in the candidate designs scheme that further data set is limited to manageability quantity.A kind of system that is used to realize method of the present invention is also disclosed simultaneously.
By below in conjunction with the detailed description of accompanying drawing to specific embodiments of the invention, other schemes of the present invention and feature will be more obvious for those of ordinary skill in the art.
Description of drawings
To and embodiments of the invention be described with reference to the accompanying drawings by embodiment below, wherein:
Fig. 1 shows the parallel coordinates figure of data in a circuit according to the invention;
Fig. 2 shows a parallel coordinates figure, and it has shown according to the present invention the visual relation between module and design variable;
Fig. 3 shows a parallel coordinates figure, and it has shown according to the present invention the visual relation between module and stochastic variable;
Fig. 4 shows a parallel coordinates figure, and it has shown according to the present invention the visual relation between module and environmental variance;
Fig. 5 shows a parallel coordinates figure, and it has shown according to the present invention the visual relation between module, stochastic variable, design variable and environmental variance;
Fig. 6 shows a parallel coordinates figure, and it has shown the visual relation of another between module, stochastic variable, design variable and environmental variance according to the present invention;
Fig. 7 shows the coordinate 9 of previous circuit data and 10 chart;
Fig. 8 to 20 shows first example according to method for visualizing of the present invention;
Figure 22 to 35 shows second example according to method for visualizing of the present invention.
Embodiment
Usually, the invention provides a kind of method and system that is used for design scheme selection by interactive mode diagram method.The present invention is suitable for learning the performance and the effect of mimic channel especially, and is used for selecting a preferred design from the candidate designs scheme data centralization that multiobjective optimization is derived.In one embodiment, the visualization processing based on the parallel coordinates system makes the user observe the trade-off analysis process of circuit module and multidimensional parameter with effective and efficient manner.Give the several method that utilizes this visualization system research circuit performance and designing quality, particularly by the synthetic design of deriving of board design.
System of the present invention generally includes the database of a storage cube, for example one group of predetermining circuit variable that is used for many potential circuit design schemes.The multi-purpose computer of carrying out the data visualization application software of a kind of well-known open source program ggobi and so on makes design variable that multidimensional data concentrates each design proposal be shown as chart on the computer monitor of routine or display.User and show that reciprocation between the graphic user interface of this chart makes data set can be under multiple form observed and be limited to the design proposal that some is wanted.User interactions can provide such as the instrument that brush pen, font selection, color treatments etc. provide such as mouse, keyboard etc. with by data visualization software with the user input device of routine, in the ggobi handbook on http://www.ggobi.org more complete description is arranged.
Embodiments of the invention can be realized with the computer programming language of any routine.For example, preferred embodiment available processes programming language (such as " C ") or object oriented language (such as C++) are realized.Optional embodiment of the present invention can be embodied as the combination of hardware element, other associated components or the hardware and software of pre-programmed.
Embodiment can be embodied as a kind of computer program of using with computer system of being used for.This realization can comprise the instruction of series of computation machine, they otherwise be fixed on the tangible medium, such as computer-readable medium (such as floppy disk, CD-ROM, ROM or fixed disk), or be transferred to computer system such as the communication adapter that is connected to network by medium through modulator-demodular unit or other interfacing equipments.
Described medium can be tangible medium (such as light or electrical communication lines) or the medium (such as microwave, infrared ray or other transmission technologys) realized with wireless technology.Described series of computation machine instruction realizes all or part of function described herein.Those skilled in the art will realize that such computer instruction can write with various programming languages, so that use with many Computer Architectures or operating system.And these instructions can be stored in any memory devices, such as semiconductor, magnetic, light or other memory devices, and can utilize any communication technology transmission, such as light, infrared ray, microwave or other transmission technologys.
Can reckon with that such computer program is as a kind of removable medium (such as the packing software of compression) issue that has written or electronic document, by computer system (such as on ROM of system or fixed disk) preload, or pass through network (such as the Internet or WWW) by server and issue.Certainly, some embodiments of the present invention can be used as the combination realization of software (such as computer program) and hardware.Other embodiment of the present invention can be fully as hardware or realize as software (such as computer program) fully.
Method of the present invention, that carry out design scheme selection by the interactive mode diagram method of cube generally comprises by multi-objective optimization method a cube, perhaps other method is provided.This cube is shown as a plurality of charts then.These charts can be one or more dimensions, and can comprise parallel coordinates figure.By revising at least one chart, the user can alternatively select a valuation data set to be used for further valuation or test.Thereby this modification can take the mode of mutual filtering to reduce data set in the mode of wanting.Typically, can utilize visual selection, the brush pen waits and realizes reducing of data set by graphical interfaces.Also can be included in the constraint function that multidimensional data is concentrated definition or created one or more variablees.This constraint can be linear or nonlinear constraint.Modification and selection course can be repeated as required with in the candidate designs scheme that further data set is limited in manageable quantity.
Usually, it should be noted that parallel coordinates figure is very effective for diagram circuit data collection, because it provides very little computation complexity O (N), wherein N is dimension (variable) number that the parallel shafts of equal number is represented, in addition, also because it is all effective for any N, wherein variable is handled by unified, and the object that shows can be discerned under projective transformation.This represents and visually surveys the compromise mimic channel data of multidimensional with regard to allowing to use based on the graphic technique of parallel coordinates, in the time limit design process of complexity is made better decision-making to help the deviser.
Parallel coordinates shows it is the leading technology of the seventies, has been applied to different multidimensional problems.In the method, each is tieed up corresponding to an axle, N the perpendicular line that axle is set to have uniform interval.Data element in the N dimension space will oneself be expressed as the set of the point of connection, each last point.The point of conllinear or coplane is created out intelligible structure in image.The main limitation of Parallel Coordinates is that big data set can cause the difficulty of decipher; Because each point produces straight line, a lot of points can cause quick hyperplasia bunch.Relation between the adjacent dimension is also understood easily than the relation between the non-adjacent dimension.The dimension that can be illustrated is quite big, but is subject to the horizontal resolution of screen, axle approaching more mutually just more the indigestion structure or bunch.The typical flat row-coordinate that Fig. 1 shows the mimic channel data set of 561 vectors shows that it comprises 21 dimensions (variable) along the horizontal line layout, and respective value is presented on the perpendicular line.Circuit index, create index and working point index respectively by layout in first, second and three-dimensional; Module is displayed in the 4th to the 15 coordinate; Stochastic variable is displayed in the 16 to the 17 coordinate; And design variable is displayed in the 18 to the 21 coordinate.By using color and dynamically brush pen and font simultaneously, the user can be easily and the information interaction that shows, thereby focus on and follow the tracks of specific data item purpose behavioural characteristic.It also is useful when hiding or getting rid of some coordinates or vector, so the deviser can easily focus on interested data.Below part how useful described about the important relationship and the relation of testing them of information visualization between research module and stochastic variable in more detail be in conjesturing.
Based on the Visual Display of parallel coordinates, the user can with visualization tool alternately to study following relation:
(see figure 2) between module and design variable.From with can obviously the finding out alternately of this chart, if two last design variables are high (coordinate 19 and 20), it is attainable having only the overshoot (coordinate 9) of little number percent.
(see figure 3) between module and stochastic variable.Randomness has little influence to the performance of circuit.
Between module and environmental variance (working point).For the module on the 5th and the 6th coordinate, there is the big (see figure 4) that influences the working point to the performance of circuit.
(see figure 5) between design variable, stochastic variable, environmental variance and module.Design proposal is greater than by the influence of working point and is subjected to make the introducing The noise.The coordinate of Fig. 5 amplifies in Fig. 6 and draws.In Fig. 6, the user can see that the line segment that connects coordinate 7 to 10 does not intersect mutually, can learn that between all modules positive correlation is arranged thus at once.Positive correlation in these coordinates between the two is shown as scatter diagram in Fig. 7.
Information shows a part that includes only the data query task as an integral part.Reason is that data visualisation system should be not only to draw data, also should have some decision analysis compositions to bear results from learn data set mutual, discern correct characteristic dimension, finds the pattern hidden and infers from the model of constructing.As special case, but trend and pattern in user's detection design data, and this will help to answer some problems about design.When making in this way, create an inquiry, with the relevant record of problem of visit with statement.After Data Receiving, check that these data are to seek to can be used for answering pattern or other useful informations of original problem.
Utilize the information and the interaction feature that show, the user can test following conjecture about concerning between the different designs variable:
The working point how by each module or all variable influence the performance of circuit candidate scheme.In case the circuit performance under the different operating condition is better understood, just can stipulates environmental parameter such as voltage and temperature range, thereby make circuit performance satisfactory.
How manufacturing environment passes through the performance of the circuit candidate scheme of each module or all variablees.This output and improvement that can be used for calculation expectation designs to obtain higher output.
Such as aspect minimum, maximum, average, intermediate value and the standard variance, for each or all working point, which kind of performance is typical at the statistical measurement item.This of great use because it has provided the good sign of minimum, typical case and the maximum performance of circuit.
In this validation task, the user produces a conjecture about data, and these data are sent inquiry, and checks the result of inquiry, to seek the positive or negative to conjesturing.In the former case, EOP (end of program); Under one situation of back, confirmed that up to this result data this conjecture or user judge that conjecture is invalid for the data that provide for the inquiry and the program loop that make new advances.Specialty Design person can find surprisingly that it is invalid that rule of thumb that they rely on comes the method for prediction circuit performance.
Method of the present invention can obtain explanation best with reference to the example of following two Analog Circuit Design Scheme Choice.Circuit module and its dependent variable in these examples, are provided, because a plurality of candidate designs scheme is derived from multiobjective optimization or synthetic technology.Each candidate designs scheme three working points by emulation.In first example, 200 candidate designs schemes are evaluated three working points, and the result is 600 data sets.In second example, 17 candidate designs schemes are evaluated on 11 random occurrences and three working points.
Then, the user changes to variable random occurrence with the X-axis of the chart of demonstration from the working point, (selects interested axle from the variable that the right-hand member that shows is listed) as shown in figure 12.A random occurrence is from Monte Carlo (Monte Carlo) sampling to extracting in the distribution of making the stochastic variable modeling the circuit.The user can see concentrating at this particular data now only a random occurrence, thereby no longer considers random occurrence in this specific design alternative.
The user turns to design standards more specifically now.For example, the user only wants the candidate designs scheme of open circuit gain more than or equal to 40dB, then with open circuit gain as an axle, at first select open circuit gain as shown in figure 13 less than 40dB have a few.Then as shown in figure 11, the user hides and gets rid of the new data point of selecting, with the chart that obtains showing among Figure 14.
When the user surveys concerning between the selected data point, can obtain knowledge about these data.For example, this user can see has one to trade off usually in velocity of wave motion with between stabilization time, as shown in figure 15.The user determines the value of the velocity of wave motion that filtering is excessive and the value of excessive stabilization time then, forms the displayed map of Figure 16.
Then, the user will find the compromise between velocity of wave motion, stabilization time and the CMRR, then select the three-dimension interaction revolved view, and spin data alternatively, shown in Figure 17 A-17C.When the CMRR composition was hidden, the user can see velocity of wave motion and familiar the trading off between stabilization time.If but rotating this view, he will see that existence is compromise between whole three variablees.The user can see: if remove the point that some have little CMRR value, will influence considerably velocity of wave motion and stabilization time performance, so at this moment he does not select based on CMRR with regard to judging.
The deviser then considers to carry out filtering based on overshoot number percent.He can see that velocity of wave motion and stabilization time are still good, thereby remove the data of all high number percent overshoots, stay 71 selected data points when overshoot number percent hour.
The deviser then uses one dimension point diagram (dotplot) research area, shown in Figure 18 A.He removes all bigger areas by selecting data then it to be hidden earlier at decision, and the result is shown in Figure 18 B.
With after many views and the many different variable browsing datas, the user determines that last selection should promptly have the design of CL bandwidth optimum value based on the CL bandwidth.By showing the one dimension chart of CL bandwidth, he at first selects data to be hidden, and then it is hidden.Form individual data point like this, shown in Figure 19 A-19B.The final data point has the mark corresponding to particular design, thereby can recover interested design, shown in Figure 19 C.
Second embodiment uses the parallel coordinates chart, and shows the user and how to analyze random variation influence in the mill, and the influence of varying environment condition of work.
In Figure 21 A-21C, will learn to have carried out what sampling in these data.In Figure 21 A, x-y illustrates 17 different candidate designs schemes, and each has 11 different random occurrences.In Figure 21 B, the user sees for each design candidate scheme 3 working points.In Figure 21 C, the user can be visual fully with enumerating of information to the three-dimensional chart of random occurrence to the working point with candidate ID.
Then, the user is circulated to check what circuit the user can remove based on the performance measurement item in some one dimension figure (these figure show density simultaneously).User's decision is removed has very all circuit of subsection gain bandwidth (GB), shown in Figure 22 A-22D.The user observes x-y figure then, and one of them axle is candidate ID, and another axle is the performance measurement item.The influence that the user often sees is for each candidate three " piece " data (corresponding piece of each environmental work point to be arranged; A piece comprises that all stochastic variables change).In Figure 23 A, the user sees that there is very big influence the working point to the input bias current of many candidate schemes, particularly compares with stochastic variable.In Figure 23 B, the user sees that the working point has less material impact to the CL bandwidth; The influence of working point and stochastic variable much at one.In Figure 23 C, the user sees that working point and stochastic variable have almost nil influence to the area of candidate scheme.This is user expectation just.In Figure 23 D, for input drift voltage, the user sees that environmental work point has influence, but stochastic variable does not have.Certainly, different design candidate schemes has the intensity of different brackets, shown in Figure 23 E.For example, the user sees, with regard to the output source electrode current, the candidate scheme on the ultra-Left end of this x-y chart is not subjected at random the influence with environmental change at all.In Figure 23 F, compare with every other circuit, the user sees for showing very poor candidate scheme for overshoot number percent under the certain environmental conditions.In Figure 23 G, the user removes this candidate scheme.
In the set of data points that reduces, the user then checks the influence of quiescent current, shown in Figure 24 A.The user sees a candidate scheme with not really strong quiescent current, so the user removes this candidate scheme in Figure 24 B.With reference to the chart of Figure 25 A, the user sees two candidate schemes with not really strong output pulsation voltage, then cancellation selected to them, shown in Figure 25 B.In Figure 26 A-26B, the user sees the candidate scheme with not really strong output source electrode current, so the user removes this candidate scheme.In Figure 27 A-27B, the user sees the candidate scheme with not really stable input bias current, so remove this candidate.In Figure 28 A-28B, the user selects to remove two candidate schemes with the highest output mesh current.The result of all these interactive modifyings has formed the set with four candidate designs schemes that is reduced.
Utilize the parallel coordinates chart, the user then analyzes trading off between four candidate schemes of residue.In Figure 29 A, candidate scheme is brushed into each all have different colors or shade and font.All four candidate schemes are presented on the parallel coordinates chart, shown in Figure 29 B.This chart makes the user can understand the performance of all aspects of each candidate scheme immediately, in a novel way with the compromise of random variation with influence visual.Please note for some performance measurement items such as area, as broad as long in fact between candidate scheme.Then different for other performance measurement items, such as input bias current, input drift electric current and input drift voltage.The user can also understand performance difference soon: for example the user can see that the candidate scheme of ring type filling clearly has the highest output mesh current less open circuit gain is still arranged.
The user can select to be primarily focused on the measurement item of several performances only, to be used for closer analysis.Because area, CL gain peak, overshoot number percent, phase margin, stabilization time and THD are for four candidate's circuit much at one, the user removes these performance measurement items from figure, shown in Figure 29 C.
The user can be by only " hide " performance that other circuit select to check a circuit in view, shown in Figure 30 A-30C.It is disposable visual more easy with the influence of stochastic variable and environmental baseline on all properties measurement item that this makes for a circuit.The user finds that for example this candidate's open circuit gain is easy to be subjected to the varying environment working point to influence and not influenced by random variation.The user can see soon that also output pulsation voltage is subjected to the influence of random variation especially.
The user can be with the parallel coordinates figure performance of two circuit relatively soon and easily on many performance measurement items once.The user determines between these two design proposals, prefer having the design proposal of less output source electrode current and less output offset electric current, so the user no longer considers another design proposal.So stay three design candidate schemes to the user, as shown in figure 31.
The user also can use the influence of more x-y charts and three-dimensional plot table look-up randomness and varying environment condition of work.The user sees that for example for all three design candidate schemes, open circuit gain is subjected to the environmental work condition influence greatly, shown in Figure 32 A-32C.
In Figure 33 A, the user sees that open circuit gain is approximate identical for each candidate scheme on each environmental work point.Therefore the user does not check the influence of open circuit gain in the parallel coordinates chart.For the input drift electric current also is like this, so the user removes it from the parallel coordinates chart, forms the chart of Figure 33 B and 33C.
Because the influence of working point is no longer so important in determining last design, the user will only check a working point from now on.The user hides other two, shown in Figure 34 A and 34B.During remaining design proposal, the user determines to select to have the design proposal of minimum output source electrode current and the highest CL bandwidth, will not have so little input bias current although the user knows on the parallel coordinates chart of control chart 35.The user is based on selecting last design proposal very soon and efficiently with different charts mutual like this.
Provided the visualization system and the method that are used for the Analog Circuit Design scheme in the superincumbent part, but should know that this method can be used for analyzing the cube in any design field.
The above embodiment of the present invention only as an example.For a person skilled in the art, do not deviate from, can change, retrofit and change certain embodiments by the uniquely defined scope of the present invention of claims.
Claims
(according to the modification of the 19th of treaty)
1. the interactive mode diagram method of a design candidate scheme that passes through to optimize is selected the method for circuit design scheme, comprising:
The cube of the candidate designs scheme of an optimization is provided, and the candidate designs scheme of this optimization is the result of multiobjective optimization;
This Multidimensional numerical of the candidate designs scheme optimized is shown as a plurality of charts; And
By carrying out reciprocation, alternatively revise among these a plurality of figure at least one, to concentrate valuation data set of identification from this multidimensional data with the candidate designs scheme of the optimization that shows.
2. according to the process of claim 1 wherein, show that a plurality of charts comprise demonstration one dimension chart.
3. according to the process of claim 1 wherein, show that a plurality of charts comprise demonstration multidimensional chart.
4. according to the method for claim 3, wherein, show that the multidimensional chart comprises the demonstration two-dimensional diagram.
5. to go 3 method according to right, wherein, show that the multidimensional chart comprises and show three-dimensional chart.
6. according to the method for claim 3, wherein, show that the multidimensional chart comprises demonstration rotation chart.
7. according to the method for claim 3, wherein, show that the multidimensional chart comprises demonstration parallel coordinates chart.
8. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises at least one the implementation filtering in described a plurality of charts.
9. according to the method for claim 8, wherein, carry out filtering and comprise at least one of brushing in a plurality of charts.
10. according to the method for claim 8, wherein, carry out the constraint function that filtering comprises the variation that defines described cube.
11. according to the method for claim 10, wherein, this constraint function is non-linear.
12. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises the mapping of creating variation.
13. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises that establishment is used to reduce the mapping of dimension.
14. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises the weighted sum of creating variation.
15. the method according to claim 1 further comprises:
Described valuation data set is shown as further valuation chart; And
Alternatively revise the further valuation chart of this demonstration, to select the valuation data set of a refining from this valuation data centralization.
16. according to the process of claim 1 wherein, this cube comprises the circuit module of deriving from multiobjective optimization.
17. according to the process of claim 1 wherein, this circuit module comprises the mimic channel module.
18. the system by the interactive mode diagram method selection circuit design scheme of cube comprises:
Be used to store the database of cube;
A display is connected to operability this database, is used for this cube is shown as a plurality of charts; And
At least one that is used for alternatively revising these a plurality of charts is to concentrate the device of selecting a valuation data set from this multidimensional data.
Claims (18)
1. the interactive mode diagram method by cube is selected the method for circuit design scheme, comprising:
A cube is provided;
Cube is shown as a plurality of charts; And
By with the cube reciprocation of described demonstration, alternatively revise at least one in described a plurality of chart, select a valuation data set to concentrate from this multidimensional data.
2. according to the process of claim 1 wherein, show that a plurality of charts comprise demonstration one dimension chart.
3. according to the process of claim 1 wherein, show that a plurality of charts comprise demonstration multidimensional chart.
4. according to the method for claim 3, wherein, show that the multidimensional chart comprises the demonstration two-dimensional diagram.
5. to go 3 method according to right, wherein, show that the multidimensional chart comprises and show three-dimensional chart.
6. according to the method for claim 3, wherein, show that the multidimensional chart comprises demonstration rotation chart.
7. according to the method for claim 3, wherein, show that the multidimensional chart comprises demonstration parallel coordinates chart.
8. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises at least one the implementation filtering in described a plurality of charts.
9. according to the method for claim 8, wherein, carry out filtering and comprise at least one of brushing in a plurality of charts.
10. according to the method for claim 8, wherein, carry out the constraint function that filtering comprises the variable that defines described cube.
11. according to the method for claim 10, wherein, this constraint function is non-linear.
12. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises the mapping of creating variable.
13. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises that establishment is used to reduce the mapping of dimension.
14. according to the process of claim 1 wherein, at least one that alternatively revise in described a plurality of chart comprises the weighted sum of creating variable.
15. the method according to claim 1 further comprises:
Described valuation data set is shown as further valuation chart; And
Alternatively revise the further valuation chart of this demonstration, to select the valuation data set of a refining from this valuation data centralization.
16. according to the process of claim 1 wherein, this cube comprises the circuit module of deriving from multiobjective optimization.
17. according to the process of claim 1 wherein, this circuit module comprises the mimic channel module.
18. the system by the interactive mode diagram method selection circuit design scheme of cube comprises:
Be used to store the database of cube;
A display is connected to operability this database, is used for this cube is shown as a plurality of charts; And
At least one that is used for alternatively revising these a plurality of charts is to concentrate the device of selecting a valuation data set from this multidimensional data.
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| US29810401P | 2001-06-15 | 2001-06-15 | |
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| CN113095427A (en) * | 2021-04-23 | 2021-07-09 | 中南大学 | High-dimensional data analysis method and face data analysis method based on user guidance |
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- 2002-06-17 CA CA002449475A patent/CA2449475A1/en not_active Abandoned
- 2002-06-17 WO PCT/CA2002/000891 patent/WO2002103582A2/en not_active Application Discontinuation
- 2002-06-17 CN CNB028119789A patent/CN1272735C/en not_active Expired - Fee Related
- 2002-06-17 US US10/479,582 patent/US20040148578A1/en not_active Abandoned
- 2002-06-17 EP EP02740166A patent/EP1402427A2/en not_active Withdrawn
- 2002-06-17 JP JP2003505829A patent/JP2004532489A/en active Pending
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| US9037273B2 (en) | 2009-04-20 | 2015-05-19 | Abb Research Ltd. | Operator terminal in a process control system |
| CN102405448B (en) * | 2009-04-20 | 2015-09-09 | Abb研究有限公司 | Operator terminal in Process Control System |
| CN104408255A (en) * | 2014-11-28 | 2015-03-11 | 浙江大学 | Single field design alternation processing method supporting five-bar robot collaborative design |
| CN104408255B (en) * | 2014-11-28 | 2017-06-20 | 浙江大学 | Support single domain design changing process method of five link robots collaborative designs |
| CN113095427A (en) * | 2021-04-23 | 2021-07-09 | 中南大学 | High-dimensional data analysis method and face data analysis method based on user guidance |
Also Published As
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| WO2002103582A2 (en) | 2002-12-27 |
| JP2004532489A (en) | 2004-10-21 |
| WO2002103582B1 (en) | 2003-12-18 |
| EP1402427A2 (en) | 2004-03-31 |
| WO2002103582A3 (en) | 2003-10-09 |
| CN1272735C (en) | 2006-08-30 |
| US20040148578A1 (en) | 2004-07-29 |
| CA2449475A1 (en) | 2002-12-27 |
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